Spiral grain, taper, butt swell, knots, growth damage, and cutting patterns are factors related to grain deviation from the longitudinal edge of a piece of lumber. Grain deviation includes surface angle and dive angle. Surface angle is the angle between the grain direction (direction of trachea axis) and the longitudinal edge on the viewing surface of the piece of lumber. Dive angle is the tilting angle of the trachea axis with respect to the surface plane. Because wood is a highly anisotropic material, the grain direction of wood has a significant effect on strength, stiffness, and dimensional stability of wood products. The grain direction measurement is very useful for twist prediction, lumber strength grading, and knot delineation. Different scanning technologies that measure grain direction primarily identify lumber defects, evaluate lumber strength, and predict lumber warp propensity. Several of these technologies rely on a phenomenon known as the “tracheid-effect” whereby patterns of light scatter (both secular and diffuse) can be interpreted to infer geometric properties of the small fibers that constitute materials such as wood. A tracheid effect (Referred to as the T1 effect) is described in U.S. Pat. No. 3,976,384. The reflected shape of a round spot of laser light will appear elongated when reflected off the surface of wood. The direction of this elongation follows the axis of the tracheids. Another example, the “T2” concept described in U.S. Pat. No. 4,606,645 involves the projection of collimated light onto a fibrous web. The direction of the strongest reflection is perpendicular to the fiber axes. For diving grains, light reflected from the side and bottom walls of open tracheids cause the locations of the highest local reflection intensity to move toward the diving direction. The reflected light on end grain or knot is scattered or diffused. These phenomena are demonstrated in FIG. 1.
As shown in FIG. 2A, a laser scanning instrument (10) made by Plessey Company (UK) includes a ring of 72sensors (12) with 5°(degree) pacing and measures the 45° (degree) light reflection (14) from a laser (16) shining straight down onto a wood surface (18).
FIG. 2B shows a schematic representation of laser light (16) striking the surface of wood (18), wherein the reflected light (14) is detected by sensors (12) arranged in a ring. An ideal plot of the reflected light intensities versus the azimuth angle around the ring has two symmetric peaks (local maximum intensities) and two valleys (local minimum intensities). Surface angle is indicated by the shift in peak locations (shown in FIG. 3). Diving or tilting brings the peaks closer together if the grain dives in the same direction, or farther apart if the grain dives in the opposite direction. As shown in FIG. 4, the peaks are closer together as the dive angle increases and the differences between the intensities at the valleys (the reflection from the bottom wall) increases with the dive angle.
The surface and dive angles can be calculated using the azimuth angle locations of these two peaks and the angle of the reflected light from the wood surface, otherwise referred to as the view angle (Matthews 1987). The applicable formulas are provided below:Surface angle=(peak1+peak2)/2−180Dive angle=arctan(tan(view angle/2)*cos((peak1−peak2)/2)
These formulas were developed based on the assumption that the distribution of the orientation of the side wall on the surface is uniform. This assumption is valid only when the grain pattern has either perfectly vertical or perfectly flat grain and results in symmetric peaks of the same height. According to the formulas, where the view angle is known, the only data needed to calculate the surface and dive angles are the positions of these two peaks. A difference in peak heights can indicate the existence of ring curvature on the wood surface, which deviates from the assumption. There are errors involved in T2 dive angle calculation when peaks are too close together, or when one peak is significantly higher than the other, or when both situations occur. These errors can be observed by measuring the same spot while tilting or rotating the sample (Schajer & Reyes 1986, Prieve 1985).
Reducing the number of sensors and improving peak finding algorithms have been frequent research subjects of the T2 technology. A simplified design using 10 sensors demonstrated that sensors can be placed at a few critical locations to achieve a sufficient accuracy with a mean error in a range from 0.5 degree to 1.8 degree (Schajer 1986). It was found that to achieve these accuracies, the ring of sensors needed to have uniform sensitivity. The use of inverse parabola interpolation schemes also greatly reduced the errors of peak finding. The observed systematic errors were also found to be larger in dive angle calculation than in the surface angle calculation (Schajer & Reyes 1986). Variations of the twin-peak intensity pattern were observed to be related to surface roughness, damages, wane, and/or sample tilting. (Prieve 1985).
Most tracheid-effect interpretation models assume that the tracheid has a circular cross-section (FIG. 11 in U.S. Pat. No. 4,606,645) and no variation in the orientation of the side walls of the opened tracheid (referred to as the “simple model of a wood surface” (Matthews 1987)).
Surface roughness, ring curvature, and dynamic measuring condition (measuring while the sample is moving) are a few of the factors that affect the consistency of the surface and dive angle measurements, especially for high dive angles. The systematic “errors” reported in previous work (Schajer & Reyes 1986) (illustrated in FIG. 5) may be effects of certain unique patterns of wood structure, and therefore may convey useful information about the structure. Note the greater systematic errors in dive angle than in surface angle prediction.
Such inconsistency in measuring dive angles around a knot tends to cause over-estimation of the size of a knot. Accurate estimation of the size of knots optimizes the recovery of clear wood from remanufacturing operations and improves the accuracy of sorting visual grades of structural lumber. The location of pith is required to estimate the size of knots within a piece of lumber. Therefore, the accuracy of knot size estimation can be improved by measuring the ring curvature or the pith location using a T2 scanning system.
Lumber twist propensity can be inferred from the dive and surface angle patterns within the clearwood (no knots) areas of the lumber. Accordingly, a need exists for a method of using T2-related information to infer clearwood locations and exclude data from non-clearwood locations. A further need exists for a method of using other information in T2 reflection patterns, combined with the knowledge of the wood surface microstructure, to find pith location and ring curvature.